Good Practices for Machine Learning

SURFsara, Amsterdam (NL)

Sep 10-11, 2019

9:00 am - 5:00 pm

Instructors: Carlos Martínez Ortiz (eScience Center), Sagar Dolas (SURFsara), Ruben Hekster (SURFsara)

Helpers: Johan Hidding (eScience Center), Maxwell Cai (SURFsara), David Ruhe (SURFsara)

Registration price for all participants (2 days): 125 Euros

General Information

Machine learning has become a hugely popular topic in the last years. Everybody is talking about it and it has shown to be very helpful for different purposes. However, which are the potential benefits of machine learning applied to research and how can machine learning methods get to be an integral part of a software project? This workshop will provide an answer to these questions.

In particular, you will get an overview of good practices that will help you start your Open Source Software project. You will get some insight on helpful tools for unit testing, package management, continuous integration and containerisation.

On the second day you will get familiar with the basics of machine learning and some advice on how to use different support libraries to build your own software project. The theory on the different types of learning will be mixed with hands-on exercises using Jupyter notebooks, which run on the systems at SURFsara.

Who: The course is aimed at graduate students and other researchers, as well as anybody who would like to learn the basics for the development of open-source software and cloud-based services.

Where: SURFsara. Science Park 140, 1098 XG Amsterdam. Room VK1/VK2. Get directions with OpenStreetMap or Google Maps.

When: Sep 10-11, 2019. Add to your Google Calendar.

Requirements: Participants must bring a laptop with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.) that they have administrative privileges on. They should have a few specific software packages installed (listed below). Participants should have at least a basic level of programming experience (preferably in Python).

Contact: Please email carlos.teijeiro@surfsara or for more information.

Contents of the course

Best practices in eScience

  • Recommendations for Open source software
  • Making packages in Python ( with cookie cutter)
  • Unit testing in python using pytest
  • Continous integration with Travis CI
  • Contenerization with Docker

Introduction to Machine Learning

  • Main concepts in artificial intelligence and machine learning
  • Types of learning and available libraries
  • Hands-on exercises on modelization and optimization
  • Data competition: challenge your knowledge!
  • (Optional) Bring your own problem and get help onsite


Day 1

09:00 - 10:30 Using OSS for research
10:30 - 10:45 Morning break
10:45 - 12:00 Packaging software
12:00 - 13:00 Lunch break
13:00 - 14:30 Unit testing and continuous integration
14:30 - 14:45 Afternoon break
14:45 - 17:00 Containers

Day 2

09:00 - 10:30 Introduction to artificial intelligence and machine learning
10:30 - 10:45 Morning break
10:45 - 12:00 Practical session - data handling, management and visualization
12:00 - 13:00 Lunch break
13:00 - 14:30 Practical session - data modeling
14:30 - 14:45 Afternoon break
14:45 - 17:00 Data challenge with competition (optional: bring your own problem!)

The catering for the lunch and morning/evening breaks will be provided by the organization.

We will use this collaborative document for chatting, taking notes, and sharing URLs and bits of code.


To participate in this SURF/eScience workshop, you will need access to the software described below. In addition, you will need an up-to-date web browser.

The Bash Shell

Bash is a commonly-used shell that gives you the power to do simple tasks more quickly.

Video Tutorial
  1. Download the Git for Windows installer.
  2. Run the installer and follow the steps below:
    1. Click on "Next" four times (two times if you've previously installed Git). You don't need to change anything in the Information, location, components, and start menu screens.
    2. Select "Use the nano editor by default" and click on "Next".
    3. Keep "Use Git from the Windows Command Prompt" selected and click on "Next". If you forgot to do this programs that you need for the workshop will not work properly. If this happens rerun the installer and select the appropriate option.
    4. Click on "Next".
    5. Keep "Checkout Windows-style, commit Unix-style line endings" selected and click on "Next".
    6. Select "Use Windows' default console window" and click on "Next".
    7. Click on "Install".
    8. Click on "Finish".
  3. If your "HOME" environment variable is not set (or you don't know what this is):
    1. Open command prompt (Open Start Menu then type cmd and press [Enter])
    2. Type the following line into the command prompt window exactly as shown:

      setx HOME "%USERPROFILE%"

    3. Press [Enter], you should see SUCCESS: Specified value was saved.
    4. Quit command prompt by typing exit then pressing [Enter]

This will provide you with both Git and Bash in the Git Bash program.

The default shell in all versions of macOS is Bash, so no need to install anything. You access Bash from the Terminal (found in /Applications/Utilities). See the Git installation video tutorial for an example on how to open the Terminal. You may want to keep Terminal in your dock for this workshop.

The default shell is usually Bash, but if your machine is set up differently you can run it by opening a terminal and typing bash. There is no need to install anything.


Git is a version control system that lets you track who made changes to what when and has options for easily updating a shared or public version of your code on You will need a supported web browser.

You will need an account at for parts of the Git lesson. Basic GitHub accounts are free. We encourage you to create a GitHub account if you don't have one already. Please consider what personal information you'd like to reveal. For example, you may want to review these instructions for keeping your email address private provided at GitHub.

Git should be installed on your computer as part of your Bash install (described above).

Video Tutorial

For OS X 10.9 and higher, install Git for Mac by downloading and running the most recent "mavericks" installer from this list. Because this installer is not signed by the developer, you may have to right click (control click) on the .pkg file, click Open, and click Open on the pop up window. After installing Git, there will not be anything in your /Applications folder, as Git is a command line program. For older versions of OS X (10.5-10.8) use the most recent available installer labelled "snow-leopard" available here.

If Git is not already available on your machine you can try to install it via your distro's package manager. For Debian/Ubuntu run sudo apt-get install git and for Fedora run sudo dnf install git.

Text Editor

When you're writing code, it's nice to have a text editor that is optimized for writing code, with features like automatic color-coding of key words. The default text editor on macOS and Linux is usually set to Vim, which is not famous for being intuitive. If you accidentally find yourself stuck in it, hit the Esc key, followed by :+Q+! (colon, lower-case 'q', exclamation mark), then hitting Return to return to the shell.

nano is a basic editor and the default that instructors use in the workshop. It is installed along with Git.

Others editors that you can use are Notepad++ or Sublime Text. Be aware that you must add its installation directory to your system path. Please ask your instructor to help you do this.

nano is a basic editor and the default that instructors use in the workshop. See the Git installation video tutorial for an example on how to open nano. It should be pre-installed.

Others editors that you can use are BBEdit or Sublime Text.

nano is a basic editor and the default that instructors use in the workshop. It should be pre-installed.

Others editors that you can use are Gedit, Kate or Sublime Text.


Python is a popular language for research computing, and great for general-purpose programming as well. Installing all of its research packages individually can be a bit difficult, so we recommend Anaconda, an all-in-one installer.

Regardless of how you choose to install it, please make sure you install Python version 3.x (e.g., 3.6 is fine).

We will teach Python using the Jupyter notebook, a programming environment that runs in a web browser. For this to work you will need a reasonably up-to-date browser. The current versions of the Chrome, Safari and Firefox browsers are all supported (some older browsers, including Internet Explorer version 9 and below, are not).

  1. Open with your web browser.
  2. Download the Python 3 installer for Linux.
    (The installation requires using the shell. If you aren't comfortable doing the installation yourself stop here and request help at the workshop.)
  3. Open a terminal window.
  4. Type
    bash Anaconda3-
    and then press Tab. The name of the file you just downloaded should appear. If it does not, navigate to the folder where you downloaded the file, for example with:
    cd Downloads
    Then, try again.
  5. Press Return. You will follow the text-only prompts. To move through the text, press Spacebar. Type yes and press enter to approve the license. Press enter to approve the default location for the files. Type yes and press enter to prepend Anaconda to your PATH (this makes the Anaconda distribution the default Python).
  6. Close the terminal window.